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SQL Server 2017 Machine Learning Services with R

You're reading from SQL Server 2017 Machine Learning Services with R Data exploration, modeling, and advanced analytics

Product type Paperback

Published in Feb 2018

Publisher Packt

ISBN-13 9781787283572

Length 338 pages

Edition 1st Edition

Languages

R

Tools

R Services

Concepts

Data Analysis

Authors (2):

Toma≈æ Ka≈°trun Kaštrun

Koesmarno

View More author details

Table of Contents (17) Chapters

Title Page

Copyright and Credits

www.PacktPub.com

Contributors

Preface

1. Introduction to R and SQL Server FREE CHAPTER

2. Overview of Microsoft Machine Learning Server and SQL Server

3. Managing Machine Learning Services for SQL Server 2017 and R

4. Data Exploration and Data Visualization

5. RevoScaleR Package

6. Predictive Modeling

7. Operationalizing R Code

8. Deploying, Managing, and Monitoring Database Solutions containing R Code

9. Machine Learning Services with R for DBAs

10. R and SQL Server 2016/2017 Features Extended

1. Other Books You May Enjoy

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Index

Functions for data preparation

Importing data is the first of the many processes in data preparation. Importing data is a process of bringing data into your system from any external system using an external file or by establishing a connection to a live data source. In the following part, we will look at importing data that is stored as SPSS or SAS files and using an ODBC connection string to connect directly to an external live database system.

Data import from SAS, SPSS, and ODBC

Importing data into R or SQL Server tables is not the main focus of RevoScaleR library, but since this is on the list, let's briefly look into it. In this manner, based on your data source, the RevoScaleR package gives many abilities to connect to different data sources. Among these are also SAS and SPSS - two very broad and common statistical programs for data analysis and predictive analytics. We will simply focus on SAS software (https://www.sas.com/), SPSS Statistics, acquired by IBM in 2009 (https://www.ibm...

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Authors (2)

Toma≈æ Ka≈°trun Kaštrun

Toma≈æ Ka≈°trun Kaštrun

Toma Katrun is a SQL Server developer and data scientist with more than 15 years of experience in the fields of business warehousing, development, ETL, database administration, and query tuning. He holds over 15 years of experience in data analysis, data mining, statistical research, and machine learning. He is a Microsoft SQL Server MVP for data platform and has been working with Microsoft SQL Server since version 2000. He is a blogger, author of many articles, a frequent speaker at the community and Microsoft events. He is an avid coffee drinker who is passionate about fixed gear bikes.

See other products by Toma≈æ Ka≈°trun Kaštrun

Koesmarno

Koesmarno

Julie Koesmarno is a senior program manager in the Database Systems Business Analytics team, at Microsoft. Currently, she leads big data analytics initiatives, driving business growth and customer success for SQL Server and Azure Data businesses. She has over 10 years of experience in data management, data warehousing, and analytics for multimillion-dollar businesses as a SQL Server developer, a system analyst, and a consultant prior to joining Microsoft. She is passionate about empowering data professionals to drive impacts for customer success and business through insights.

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